cos_e / cos_e.py
# coding=utf-8
# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# Lint as: python3
"""Commonsense Explanations (CoS-E) Dataset."""
import json
import datasets
_CITATION = """
@inproceedings{rajani2019explain,
title = {Explain Yourself! Leveraging Language models for Commonsense Reasoning},
author = {Rajani, Nazneen Fatema and
McCann, Bryan and
Xiong, Caiming and
Socher, Richard}
year={2019}
booktitle = {Proceedings of the 2019 Conference of the Association for Computational Linguistics (ACL2019)}
url ={https://arxiv.org/abs/1906.02361}
}
"""
_DESCRIPTION = """
Common Sense Explanations (CoS-E) allows for training language models to
automatically generate explanations that can be used during training and
inference in a novel Commonsense Auto-Generated Explanation (CAGE) framework.
"""
_COS_E_URL = "https://raw.githubusercontent.com/salesforce/cos-e/master/data/"
# COS E has explanations for the CQA dataset, which is joined by ID.
_CQA_V1_11_URL_TRAIN = "https://s3.amazonaws.com/commensenseqa/train_rand_split.jsonl"
_CQA_V1_11_URL_DEV = "https://s3.amazonaws.com/commensenseqa/dev_rand_split.jsonl"
_CQA_V1_11_URL_TEST = "https://s3.amazonaws.com/commensenseqa/test_rand_split_no_answers.jsonl"
_CQA_V1_0_URL_TRAIN = _COS_E_URL + "v1.0/train_rand_split.jsonl"
_CQA_V1_0_URL_DEV = _COS_E_URL + "v1.0/dev_rand_split.jsonl"
_CQA_V1_0_URL_TEST = _COS_E_URL + "v1.0/test_rand_split_no_answers.jsonl"
def _download_and_index_cqa(dl_manager, name):
"""Downloads CQA and returns it, indexed by id, for joining with Cos-E."""
downloaded_files = dl_manager.download_and_extract(
{
"cqa_train": _CQA_V1_11_URL_TRAIN if name == "v1.11" else _CQA_V1_0_URL_TRAIN,
"cqa_dev": _CQA_V1_11_URL_DEV if name == "v1.11" else _CQA_V1_0_URL_DEV,
"cqa_test": _CQA_V1_11_URL_TEST if name == "v1.11" else _CQA_V1_0_URL_TEST,
}
)
# NB: "cqa_test" is included in the files, but not in any of the CoS-E splits.
cqa_splits = ["cqa_train", "cqa_dev"]
cqa_complete = []
for split in cqa_splits:
with open(downloaded_files[split], encoding="utf-8") as f:
for _, line in enumerate(f):
d = json.loads(line)
cqa_complete.append(d)
# Index the CQA dataset by id for joining with Cos-E.
cqa_indexed = {}
for d in cqa_complete:
cqa_indexed[d["id"]] = d
return cqa_indexed
def _get_choices_and_answer(cqa):
"""Returns choices and the answer from a cqa example."""
choices = []
answer_key = cqa["answerKey"]
answer = None
for choice in cqa["question"]["choices"]:
choices.append(choice["text"])
if answer_key == choice["label"]:
answer = choice["text"]
return choices, answer
class CosEConfig(datasets.BuilderConfig):
"""BuilderConfig for CosE"""
def __init__(self, **kwargs):
"""
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(CosEConfig, self).__init__(**kwargs)
class CosE(datasets.GeneratorBasedBuilder):
"""CoS-E: Common Sense Explanations corpus."""
BUILDER_CONFIGS = [
CosEConfig(
name="v1.0",
description="cos-e version 1.0",
version=datasets.Version("1.0.0", ""),
),
CosEConfig(
name="v1.11",
description="cos-e version 1.11",
version=datasets.Version("1.11.0", ""),
),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"id": datasets.Value("string"),
"question": datasets.Value("string"),
"choices": datasets.features.Sequence(datasets.Value("string")),
"answer": datasets.Value("string"),
"abstractive_explanation": datasets.Value("string"),
"extractive_explanation": datasets.Value("string"),
}
),
supervised_keys=None,
homepage="https://github.com/salesforce/cos-e",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
# NB: The CQA Dataset should be read only once, and only by callers who
# want to _create_ the Cos-E dataset from scratch.
cqa_indexed = _download_and_index_cqa(dl_manager, self.config.name)
if self.config.name == "v1.11":
files = dl_manager.download_and_extract(
{
"dev": [_COS_E_URL + "v1.11/cose_dev_v1.11_processed.jsonl"],
"train": [_COS_E_URL + "v1.11/cose_train_v1.11_processed.jsonl"],
}
)
elif self.config.name == "v1.0":
files = dl_manager.download_and_extract(
{
"dev": [_COS_E_URL + "v1.0/cose_dev_v1.0_processed.jsonl"],
"train": [_COS_E_URL + "v1.0/cose_train_v1.0_processed.jsonl"],
}
)
else:
raise ValueError("Unknown config name")
# We use the CoS-E/CQA dev set as our validation set.
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"files": files["train"], "cqa_indexed": cqa_indexed},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"files": files["dev"], "cqa_indexed": cqa_indexed},
),
]
def _generate_examples(self, files, **kwargs):
"""Yields examples."""
cqa_indexed = kwargs["cqa_indexed"]
for filepath in files:
with open(filepath, encoding="utf-8") as f:
for line in f:
cos = json.loads(line)
cqa = cqa_indexed[cos["id"]]
choices, answer = _get_choices_and_answer(cqa)
yield cos["id"], {
"id": cos["id"],
"question": cqa["question"]["stem"],
"choices": choices,
"answer": answer,
"abstractive_explanation": cos["explanation"]["open-ended"],
"extractive_explanation": cos["explanation"]["selected"],
}